None

Clindamycin

Vancomycin

Ciprofloxacin

Ampicillin

Cefaperazone

Metronidazole

Streptomycin

diversity vs colonization

alpha diversity

communities colonized to higher levels have lower diversity (alpha)

association between cfu and alpha (invsimpson and shannon - NS)

cfu vs # of otus (NS)

shared otus?

beta diversity

highly infected communities are most different than untreated

separation between untreated mice and all the highly infected communities (>1e6)

communities that recover/elimnate cdifficile are more diverse

difference in diversity between highly infected

more change w/low diversity?

more change with high cfu?

need to remove dependence of daily sampling?

Alpha Diversity

## [[1]]

## [[1]]
## 
## Call:
## lm(formula = get(variable_name) ~ CFU, data = data_frame)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -3.331 -3.077 -1.845  1.670 28.555 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  3.337e+00  9.199e-02  36.277  < 2e-16 ***
## CFU         -1.136e-08  1.903e-09  -5.972 2.69e-09 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4.2 on 2426 degrees of freedom
##   (130 observations deleted due to missingness)
## Multiple R-squared:  0.01449,    Adjusted R-squared:  0.01408 
## F-statistic: 35.66 on 1 and 2426 DF,  p-value: 2.693e-09
## [[1]]

## [[1]]
## 
## Call:
## lm(formula = get(variable_name) ~ CFU, data = data_frame)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -27.83 -25.29 -12.67  21.22 195.27 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  2.916e+01  6.536e-01  44.616  < 2e-16 ***
## CFU         -6.609e-08  1.352e-08  -4.888 1.09e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 29.84 on 2426 degrees of freedom
##   (130 observations deleted due to missingness)
## Multiple R-squared:  0.009751,   Adjusted R-squared:  0.009343 
## F-statistic: 23.89 on 1 and 2426 DF,  p-value: 1.087e-06
## [[1]]

## [[1]]
## 
## Call:
## lm(formula = get(variable_name) ~ CFU, data = data_frame)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -1.0640 -1.0409 -0.5456  1.0386  3.3083 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  1.076e+00  2.473e-02  43.499  < 2e-16 ***
## CFU         -2.068e-09  5.116e-10  -4.042 5.46e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.129 on 2426 degrees of freedom
##   (130 observations deleted due to missingness)
## Multiple R-squared:  0.00669,    Adjusted R-squared:  0.00628 
## F-statistic: 16.34 on 1 and 2426 DF,  p-value: 5.463e-05
## [[1]]

## [[1]]
## 
## Call:
## lm(formula = get(variable_name) ~ CFU, data = data_frame)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -2.474 -2.302 -1.224  1.509 29.398 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  2.481e+00  8.673e-02  28.601  < 2e-16 ***
## CFU         -4.698e-09  1.478e-09  -3.178  0.00151 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3.132 on 1646 degrees of freedom
##   (89 observations deleted due to missingness)
## Multiple R-squared:  0.006098,   Adjusted R-squared:  0.005494 
## F-statistic:  10.1 on 1 and 1646 DF,  p-value: 0.001511
## [[1]]

## [[1]]
## 
## Call:
## lm(formula = get(variable_name) ~ CFU, data = data_frame)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -23.21 -20.92 -12.96  17.59 194.36 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  2.441e+01  7.030e-01  34.720   <2e-16 ***
## CFU         -2.910e-08  1.198e-08  -2.428   0.0153 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 25.39 on 1646 degrees of freedom
##   (89 observations deleted due to missingness)
## Multiple R-squared:  0.00357,    Adjusted R-squared:  0.002964 
## F-statistic: 5.897 on 1 and 1646 DF,  p-value: 0.01527
## [[1]]

## [[1]]
## 
## Call:
## lm(formula = get(variable_name) ~ CFU, data = data_frame)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -0.9334 -0.9090 -0.5984  0.9040  3.2837 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  9.469e-01  2.745e-02  34.500   <2e-16 ***
## CFU         -1.065e-09  4.678e-10  -2.277   0.0229 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9912 on 1646 degrees of freedom
##   (89 observations deleted due to missingness)
## Multiple R-squared:  0.00314,    Adjusted R-squared:  0.002534 
## F-statistic: 5.185 on 1 and 1646 DF,  p-value: 0.02291